# spatstat v1.41-1

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## Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests

Comprehensive toolbox for analysing spatial data, mainly Spatial Point Patterns, including multitype/marked points and spatial covariates, in any two-dimensional spatial region. Also supports three-dimensional point patterns, space-time point patterns in any number of dimensions, and point patterns on a linear network.
Contains about 2000 functions for plotting spatial data, exploratory data analysis, model-fitting, simulation, spatial sampling, model diagnostics, and formal inference.
Data types include point patterns, line segment patterns, spatial windows, pixel images, tessellations, and linear networks.
Exploratory methods include quadrat counts, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Diggle-Cressie-Loosmore-Ford, Dao-Genton) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov) are also supported.
Parametric models can be fitted to point pattern data using the functions ppm, kppm, slrm similar to glm. Types of models include Poisson, Gibbs, Cox and cluster point processes. Models may involve dependence on covariates, interpoint interaction, cluster formation and dependence on marks. Models are fitted by maximum likelihood, logistic regression, minimum contrast, and composite likelihood methods.
Fitted point process models can be simulated, automatically. Formal hypothesis tests of a fitted model are supported (likelihood ratio test, analysis of deviance, Monte Carlo tests) along with basic tools for model selection (stepwise, AIC). Tools for validating the fitted model include simulation envelopes, residuals, residual plots and Q-Q plots, leverage and influence diagnostics, partial residuals, and added variable plots.

## Functions in spatstat

Name | Description | |

edges2vees | List Dihedral Triples in a Graph | |

clickdist | Interactively Measure Distance | |

Extract.fv | Extract or Replace Subset of Function Values | |

panel.contour | Panel Plots using Colour Image or Contour Lines | |

marks.psp | Marks of a Line Segment Pattern | |

lut | Lookup Tables | |

Gdot | Multitype Nearest Neighbour Distance Function (i-to-any) | |

gauss.hermite | Gauss-Hermite Quadrature Approximation to Expectation for Normal Distribution | |

linearpcfcross.inhom | Inhomogeneous Multitype Pair Correlation Function (Cross-type) for Linear Point Pattern | |

pairdist.pp3 | Pairwise distances in Three Dimensions | |

circdensity | Density Estimation for Circular Data | |

exactMPLEstrauss | Exact Maximum Pseudolikelihood Estimate for Stationary Strauss Process | |

markconnect | Mark Connection Function | |

complement.owin | Take Complement of a Window | |

anova.ppm | ANOVA for Fitted Point Process Models | |

is.marked | Test Whether Marks Are Present | |

SatPiece | Piecewise Constant Saturated Pairwise Interaction Point Process Model | |

coords | Extract or Change Coordinates of a Spatial or Spatiotemporal Point Pattern | |

compatible.fv | Test Whether Function Objects Are Compatible | |

edges | Extract Boundary Edges of a Window. | |

intensity.lpp | Empirical Intensity of Point Pattern on Linear Network | |

cdf.test | Spatial Distribution Test for Point Pattern or Point Process Model | |

disc | Circular Window | |

logLik.slrm | Loglikelihood of Spatial Logistic Regression | |

Extract.fasp | Extract Subset of Function Array | |

Finhom | Inhomogeneous Empty Space Function | |

Fiksel | The Fiksel Interaction | |

Lcross | Multitype L-function (cross-type) | |

Math.im | S3 Group Generic methods for images | |

Poisson | Poisson Point Process Model | |

Kdot | Multitype K Function (i-to-any) | |

Smooth.ppp | Spatial smoothing of observations at irregular points | |

Emark | Diagnostics for random marking | |

Kscaled | Locally Scaled K-function | |

Lest | L-function | |

as.linnet.linim | Extract Linear Network from Data on a Linear Network | |

Pairwise | Generic Pairwise Interaction model | |

area.owin | Area of a Window | |

HierStrauss | The Hierarchical Strauss Point Process Model | |

Extract.quad | Subset of Quadrature Scheme | |

as.fv | Convert Data To Class fv | |

Jmulti | Marked J Function | |

affine.lpp | Apply Geometrical Transformations to Point Pattern on a Linear Network | |

applynbd | Apply Function to Every Neighbourhood in a Point Pattern | |

Extract.ppx | Extract Subset of Multidimensional Point Pattern | |

G3est | Nearest Neighbour Distance Distribution Function of a Three-Dimensional Point Pattern | |

as.hyperframe.ppx | Extract coordinates and marks of multidimensional point pattern | |

LambertW | Lambert's W Function | |

Kmulti.inhom | Inhomogeneous Marked K-Function | |

bei | Tropical rain forest trees | |

Kcross.inhom | Inhomogeneous Cross K Function | |

Extract.anylist | Extract or Replace Subset of a List of Things | |

Kmulti | Marked K-Function | |

affine.linnet | Apply Geometrical Transformations to a Linear Network | |

discretise | Safely Convert Point Pattern Window to Binary Mask | |

BadGey | Hybrid Geyer Point Process Model | |

affine.ppp | Apply Affine Transformation To Point Pattern | |

Triplets | The Triplet Point Process Model | |

Jinhom | Inhomogeneous J-function | |

Kovesi | Colour Sequences with Uniform Perceptual Contrast | |

as.data.frame.psp | Coerce Line Segment Pattern to a Data Frame | |

Gcross | Multitype Nearest Neighbour Distance Function (i-to-j) | |

LennardJones | The Lennard-Jones Potential | |

MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model | |

as.linnet.psp | Convert Line Segment Pattern to Linear Network | |

centroid.owin | Centroid of a window | |

MultiHard | The Multitype Hard Core Point Process Model | |

Kinhom | Inhomogeneous K-function | |

by.ppp | Apply a Function to a Point Pattern Broken Down by Factor | |

as.data.frame.ppp | Coerce Point Pattern to a Data Frame | |

bdist.tiles | Distance to Boundary of Window | |

as.data.frame.hyperframe | Coerce Hyperframe to Data Frame | |

Extract.splitppp | Extract or Replace Sub-Patterns | |

affine.im | Apply Affine Transformation To Pixel Image | |

anova.mppm | ANOVA for Fitted Multiple Point Process Models | |

Saturated | Saturated Pairwise Interaction model | |

Tstat | Third order summary statistic | |

Extract.lpp | Extract Subset of Point Pattern on Linear Network | |

areaLoss | Difference of Disc Areas | |

demohyper | Demonstration Example of Hyperframe of Spatial Data | |

DiggleGratton | Diggle-Gratton model | |

Extract.tess | Extract or Replace Subset of Tessellation | |

Fest | Estimate the Empty Space Function or its Hazard Rate | |

bdspots | Breakdown Spots in Microelectronic Materials | |

closepairs.pp3 | Close Pairs of Points in 3 Dimensions | |

crossdist.lpp | Pairwise distances between two point patterns on a linear network | |

density.ppp | Kernel Smoothed Intensity of Point Pattern | |

gridcentres | Rectangular grid of points | |

Ksector | Sector K-function | |

Window | Extract or Change the Window of a Spatial Object | |

Lcross.inhom | Inhomogeneous Cross Type L Function | |

cbind.hyperframe | Combine Hyperframes by Rows or by Columns | |

coef.slrm | Coefficients of Fitted Spatial Logistic Regression Model | |

commonGrid | Determine A Common Spatial Domain And Pixel Resolution | |

as.tess | Convert Data To Tessellation | |

affine.psp | Apply Affine Transformation To Line Segment Pattern | |

convexhull | Convex Hull | |

Extract.leverage.ppm | Extract Subset of Leverage Object | |

Geyer | Geyer's Saturation Point Process Model | |

Ldot.inhom | Inhomogeneous Multitype L Dot Function | |

Ord | Generic Ord Interaction model | |

MultiStrauss | The Multitype Strauss Point Process Model | |

anylist | List of Objects | |

Kres | Residual K Function | |

clickjoin | Interactively join vertices on a plot | |

as.function.fv | Convert Function Value Table to Function | |

closing | Morphological Closing | |

Replace.im | Reset Values in Subset of Image | |

StraussHard | The Strauss / Hard Core Point Process Model | |

Jdot | Multitype J Function (i-to-any) | |

Concom | The Connected Component Process Model | |

Jest | Estimate the J-function | |

Extract.linnet | Extract Subset of Linear Network | |

Math.linim | S3 Group Generic Methods for Images on a Linear Network | |

Linhom | L-function | |

copper | Berman-Huntington points and lines data | |

Smoothfun.ppp | Smooth Interpolation of Marks as a Spatial Function | |

Kmeasure | Reduced Second Moment Measure | |

Gfox | Foxall's Distance Functions | |

Extract.msr | Extract Subset of Signed or Vector Measure | |

as.mask.psp | Convert Line Segment Pattern to Binary Pixel Mask | |

anova.lppm | ANOVA for Fitted Point Process Models on Linear Network | |

border | Border Region of a Window | |

as.owin | Convert Data To Class owin | |

PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model | |

bramblecanes | Hutchings' Bramble Canes data | |

crossdist.default | Pairwise distances between two different sets of points | |

connected.ppp | Connected components of a point pattern | |

allstats | Calculate four standard summary functions of a point pattern. | |

diagnose.ppm | Diagnostic Plots for Fitted Point Process Model | |

as.im | Convert to Pixel Image | |

Smooth.fv | Apply Smoothing to Function Values | |

demopat | Artificial Data Point Pattern | |

discpartarea | Area of Part of Disc | |

clickppp | Interactively Add Points | |

areaGain | Difference of Disc Areas | |

eval.fasp | Evaluate Expression Involving Function Arrays | |

coef.mppm | Coefficients of Point Process Model Fitted to Multiple Point Patterns | |

bdist.pixels | Distance to Boundary of Window | |

cells | Biological Cells Point Pattern | |

endpoints.psp | Endpoints of Line Segment Pattern | |

bw.frac | Bandwidth Selection Based on Window Geometry | |

contour.im | Contour plot of pixel image | |

diameter.owin | Diameter of a Window | |

beginner | Print Introduction For Beginners | |

distmap | Distance Map | |

fv.object | Function Value Table | |

distmap.psp | Distance Map of Line Segment Pattern | |

as.polygonal | Convert a Window to a Polygonal Window | |

compatible.im | Test Whether Pixel Images Are Compatible | |

data.ppm | Extract Original Data from a Fitted Point Process Model | |

Extract.solist | Extract or Replace Subset of a List of Spatial Objest | |

WindowOnly | Extract Window of Spatial Object | |

Extract.hyperframe | Extract or Replace Subset of Hyperframe | |

domain | Extract the Domain of any Spatial Object | |

miplot | Morisita Index Plot | |

dclf.progress | Progress Plot of Test of Spatial Pattern | |

im.object | Class of Images | |

chop.tess | Subdivide a Window or Tessellation using a Set of Lines | |

circumradius | Circumradius of a Window | |

ants | Harkness-Isham ants' nests data | |

clmfires | Castilla-La Mancha Forest Fires | |

OrdThresh | Ord's Interaction model | |

mucosa | Cells in Gastric Mucosa | |

affine.tess | Apply Geometrical Transformation To Tessellation | |

diameter.box3 | Geometrical Calculations for Three-Dimensional Box | |

cauchy.estpcf | Fit the Neyman-Scott cluster process with Cauchy kernel | |

as.rectangle | Window Frame | |

deriv.fv | Calculate Derivative of Function Values | |

as.matrix.im | Convert Pixel Image to Matrix or Array | |

convexhull.xy | Convex Hull of Points | |

heather | Diggle's Heather Data | |

dirichlet.weights | Compute Quadrature Weights Based on Dirichlet Tessellation | |

formula.ppm | Model Formulae for Gibbs Point Process Models | |

edge.Trans | Translation Edge Correction | |

Extract.psp | Extract Subset of Line Segment Pattern | |

finpines | Pine saplings in Finland. | |

as.matrix.owin | Convert Pixel Image to Matrix | |

dummify | Convert Data to Numeric Values by Constructing Dummy Variables | |

beachcolours | Create Colour Scheme for a Range of Numbers | |

as.psp | Convert Data To Class psp | |

dirichlet | Dirichlet Tessellation of Point Pattern | |

clusterfield | Field of clusters | |

fvnames | Abbreviations for Groups of Columns in Function Value Table | |

is.ppm | Test Whether An Object Is A Fitted Point Process Model | |

Extract.ppp | Extract or Replace Subset of Point Pattern | |

grow.rectangle | Add margins to rectangle | |

bw.ppl | Likelihood Cross Validation Bandwidth Selection for Kernel Density | |

angles.psp | Orientation Angles of Line Segments | |

Hardcore | The Hard Core Point Process Model | |

nncross.pp3 | Nearest Neighbours Between Two Patterns in 3D | |

im.apply | Apply Function Pixelwise to List of Images | |

compatible | Test Whether Objects Are Compatible | |

corners | Corners of a rectangle | |

connected | Connected components | |

as.mask | Pixel Image Approximation of a Window | |

as.data.frame.im | Convert Pixel Image to Data Frame | |

dirichlet.vertices | Vertices and Edges of Dirichlet Tessellation | |

methods.lpp | Methods for Point Patterns on a Linear Network | |

anemones | Beadlet Anemones Data | |

Kmark | Mark-Weighted K Function | |

infline | Infinite Straight Lines | |

plot.ppm | plot a Fitted Point Process Model | |

amacrine | Hughes' Amacrine Cell Data | |

bounding.box.xy | Convex Hull of Points | |

funxy | Spatial Function Class | |

fv | Create a Function Value Table | |

anova.slrm | Analysis of Deviance for Spatial Logistic Regression Models | |

bw.smoothppp | Cross Validated Bandwidth Selection for Spatial Smoothing | |

clusterfit | Fit Cluster or Cox Point Process Model via Minimum Contrast | |

convolve.im | Convolution of Pixel Images | |

Kcom | Model Compensator of K Function | |

density.psp | Kernel Smoothing of Line Segment Pattern | |

hist.im | Histogram of Pixel Values in an Image | |

hybrid.family | Hybrid Interaction Family | |

nnorient | Nearest Neighbour Orientation Distribution | |

linearpcfinhom | Inhomogeneous Linear Pair Correlation Function | |

eem | Exponential Energy Marks | |

Smooth | Spatial smoothing of data | |

is.marked.ppp | Test Whether A Point Pattern is Marked | |

is.im | Test Whether An Object Is A Pixel Image | |

inside.owin | Test Whether Points Are Inside A Window | |

fardist | Farthest Distance to Boundary of Window | |

deltametric | Delta Metric | |

is.ppp | Test Whether An Object Is A Point Pattern | |

bw.diggle | Cross Validated Bandwidth Selection for Kernel Density | |

eval.fv | Evaluate Expression Involving Functions | |

progressreport | Print Progress Reports | |

pppmatching.object | Class of Point Matchings | |

increment.fv | Increments of a Function | |

bw.scott | Scott's Rule for Bandwidth Selection for Kernel Density | |

clickpoly | Interactively Define a Polygon | |

identify.psp | Identify Segments in a Line Segment Pattern | |

distcdf | Distribution Function of Interpoint Distance | |

Iest | Estimate the I-function | |

levelset | Level Set of a Pixel Image | |

harmonise.im | Make Pixel Images Compatible | |

rescale.ppp | Convert Point Pattern to Another Unit of Length | |

as.ppp | Convert Data To Class ppp | |

nbfires | Point Patterns of New Brunswick Forest Fires | |

scanLRTS | Likelihood Ratio Test Statistic for Scan Test | |

is.dppm | Recognise Fitted Determinantal Point Process Models | |

Frame | Extract or Change the Containing Rectangle of a Spatial Object | |

fasp.object | Function Arrays for Spatial Patterns | |

Kest | K-function | |

linearKinhom | Inhomogeneous Linear K Function | |

Kcross | Multitype K Function (Cross-type) | |

Jcross | Multitype J Function (i-to-j) | |

marks.tess | Marks of a Tessellation | |

clarkevans.test | Clark and Evans Test | |

clip.infline | Intersect Infinite Straight Lines with a Window | |

harmonise.fv | Make Function Tables Compatible | |

diameter | Diameter of an Object | |

layered | Create List of Plotting Layers | |

is.owin | Test Whether An Object Is A Window | |

pcfcross.inhom | Inhomogeneous Multitype Pair Correlation Function (Cross-Type) | |

hamster | Aherne's hamster tumour data | |

overlap.owin | Compute Area of Overlap | |

markstat | Summarise Marks in Every Neighbourhood in a Point Pattern | |

formula.fv | Extract or Change the Plot Formula for a Function Value Table | |

crossdist.ppx | Pairwise Distances Between Two Different Multi-Dimensional Point Patterns | |

pairorient | Point Pair Orientation Distribution | |

midpoints.psp | Midpoints of Line Segment Pattern | |

is.multitype.ppp | Test Whether A Point Pattern is Multitype | |

flipxy | Exchange X and Y Coordinates | |

mean.im | Maximum, Minimum, Mean, Median, Range or Sum of Pixel Values in an Image | |

dclf.test | Diggle-Cressie-Loosmore-Ford and Maximum Absolute Deviation Tests | |

is.empty | Test Whether An Object Is Empty | |

localpcf | Local pair correlation function | |

ganglia | Beta Ganglion Cells in Cat Retina, Old Version | |

dmixpois | Mixed Poisson Distribution | |

osteo | Osteocyte Lacunae Data: Replicated Three-Dimensional Point Patterns | |

perspPoints | Draw Points or Lines on a Surface Viewed in Perspective | |

Kmodel.ppm | K Function or Pair Correlation Function of Gibbs Point Process model | |

pcfinhom | Inhomogeneous Pair Correlation Function | |

nndist | Nearest neighbour distances | |

foo | Foo is Not a Variable | |

eval.im | Evaluate Expression Involving Pixel Images | |

ponderosa | Ponderosa Pine Tree Point Pattern | |

methods.pp3 | Methods for three-dimensional point patterns | |

is.rectangle | Determine Type of Window | |

markvario | Mark Variogram | |

as.interact | Extract Interaction Structure | |

npfun | Dummy Function Returns Number of Points | |

linearKdot.inhom | Inhomogeneous multitype K Function (Dot-type) for Linear Point Pattern | |

pairdist.ppp | Pairwise distances | |

pixelquad | Quadrature Scheme Based on Pixel Grid | |

intensity.ppp | Empirical Intensity of Point Pattern | |

longleaf | Longleaf Pines Point Pattern | |

incircle | Find Largest Circle Inside Window | |

nncorr | Nearest-Neighbour Correlation Indices of Marked Point Pattern | |

persp.im | Perspective Plot of Pixel Image | |

matclust.estpcf | Fit the Matern Cluster Point Process by Minimum Contrast Using Pair Correlation | |

idw | Inverse-distance weighted smoothing of observations at irregular points | |

leverage.ppm | Leverage Measure for Spatial Point Process Model | |

profilepl | Profile Maximum Pseudolikelihood or AIC | |

clusterradius | Compute or Extract Effective Range of Cluster Kernel | |

iplot | Point and Click Interface for Displaying Spatial Data | |

kaplan.meier | Kaplan-Meier Estimator using Histogram Data | |

envelope.envelope | Recompute Envelopes | |

plot.anylist | Plot a List of Things | |

pairdist.psp | Pairwise distances between line segments | |

pool.envelope | Pool Data from Several Envelopes | |

lgcp.estK | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |

methods.rhohat | Methods for Intensity Functions of Spatial Covariate | |

nnwhich.pp3 | Nearest neighbours in three dimensions | |

plot.listof | Plot a List of Things | |

residualspaper | Data and Code From JRSS Discussion Paper on Residuals | |

plot.lpp | Plot Point Pattern on Linear Network | |

default.rmhcontrol | Set Default Control Parameters for Metropolis-Hastings Algorithm. | |

project.ppm | Force Point Process Model to be Valid | |

plot.linnet | Plot a linear network | |

distmap.ppp | Distance Map of Point Pattern | |

lpp | Create Point Pattern on Linear Network | |

pool | Pool Data | |

coef.ppm | Coefficients of Fitted Point Process Model | |

ppm | Fit Point Process Model to Data | |

gorillas | Gorilla Nesting Sites | |

invoke.symbolmap | Plot Data Using Graphics Symbol Map | |

edges2triangles | List Triangles in a Graph | |

clarkevans | Clark and Evans Aggregation Index | |

spatstat.options | Internal Options in Spatstat Package | |

pairdist.lpp | Pairwise shortest-path distances between points on a linear network | |

rMosaicField | Mosaic Random Field | |

is.subset.owin | Determine Whether One Window is Contained In Another | |

plot.quadrattest | Display the result of a quadrat counting test. | |

linearK | Linear K Function | |

model.matrix.slrm | Extract Design Matrix from Spatial Logistic Regression Model | |

nncross.lpp | Nearest Neighbours on a Linear Network | |

mincontrast | Method of Minimum Contrast | |

pcfdot | Multitype pair correlation function (i-to-any) | |

plot.symbolmap | Plot a Graphics Symbol Map | |

is.convex | Test Whether a Window is Convex | |

hierpair.family | Hierarchical Pairwise Interaction Process Family | |

pcfcross | Multitype pair correlation function (cross-type) | |

ellipse | Elliptical Window. | |

nnwhich.ppx | Nearest Neighbours in Any Dimensions | |

as.hyperframe | Convert Data to Hyperframe | |

quadrat.test.splitppp | Dispersion Test of CSR for Split Point Pattern Based on Quadrat Counts | |

quadrats | Divide Region into Quadrats | |

interp.colourmap | Interpolate smoothly between specified colours | |

cut.ppp | Classify Points in a Point Pattern | |

intensity.ppm | Intensity of Fitted Point Process Model | |

psp | Create a Line Segment Pattern | |

plot.linim | Plot Pixel Image on Linear Network | |

model.depends | Identify Covariates Involved in each Model Term | |

is.multitype | Test whether Object is Multitype | |

envelope.pp3 | Simulation Envelopes of Summary Function for 3D Point Pattern | |

plot.im | Plot a Pixel Image | |

rescale | Convert dataset to another unit of length | |

model.matrix.ppm | Extract Design Matrix from Point Process Model | |

rlinegrid | Generate grid of parallel lines with random displacement | |

npoints | Number of Points in a Point Pattern | |

quad.object | Class of Quadrature Schemes | |

print.psp | Print Brief Details of a Line Segment Pattern Dataset | |

km.rs | Kaplan-Meier and Reduced Sample Estimator using Histograms | |

methods.lppm | Methods for Fitted Point Process Models on a Linear Network | |

plot.mppm | plot a Fitted Multiple Point Process Model | |

project2segment | Move Point To Nearest Line | |

markcorr | Mark Correlation Function | |

hopskel | Hopkins-Skellam Test | |

lansing | Lansing Woods Point Pattern | |

interp.im | Interpolate a Pixel Image | |

pcf.fv | Pair Correlation Function obtained from K Function | |

pool.fv | Pool Several Functions | |

plot.leverage.ppm | Plot Leverage Function | |

pcf.fasp | Pair Correlation Function obtained from array of K functions | |

plot.envelope | Plot a Simulation Envelope | |

psp.object | Class of Line Segment Patterns | |

lurking | Lurking variable plot | |

owin.object | Class owin | |

erosion | Morphological Erosion | |

matclust.estK | Fit the Matern Cluster Point Process by Minimum Contrast | |

nndist.pp3 | Nearest neighbour distances in three dimensions | |

delaunay.distance | Distance on Delaunay Triangulation | |

by.im | Apply Function to Image Broken Down by Factor | |

methods.linfun | Methods for Functions on Linear Network | |

plot.slrm | Plot a Fitted Spatial Logistic Regression | |

summary.quad | Summarizing a Quadrature Scheme | |

marks | Marks of a Point Pattern | |

linearpcf | Linear Pair Correlation Function | |

pcf.ppp | Pair Correlation Function of Point Pattern | |

moribund | Outdated Functions | |

methods.linnet | Methods for Linear Networks | |

msr | Signed or Vector-Valued Measure | |

plot.yardstick | Plot a Yardstick or Scale Bar | |

harmonise | Make Objects Compatible | |

plot.onearrow | Plot an Arrow | |

opening | Morphological Opening | |

clusterkernel | Extract Cluster Offspring Kernel | |

logLik.mppm | Log Likelihood for Poisson Point Process Model | |

integral.linim | Integral on a Linear Network | |

pool.quadrattest | Pool Several Quadrat Tests | |

pool.rat | Pool Data from Several Ratio Objects | |

expand.owin | Apply Expansion Rule | |

distmap.owin | Distance Map of Window | |

rescale.psp | Convert Line Segment Pattern to Another Unit of Length | |

plot.ppp | plot a Spatial Point Pattern | |

betacells | Beta Ganglion Cells in Cat Retina | |

plot.quad | Plot a Spatial Quadrature Scheme | |

paracou | Kimboto trees at Paracou, French Guiana | |

project2set | Find Nearest Point in a Region | |

matchingdist | Distance for a Point Pattern Matching | |

rMaternII | Simulate Matern Model II | |

maxnndist | Compute Minimum or Maximum Nearest-Neighbour Distance | |

range.fv | Range of Function Values | |

nnclean | Nearest Neighbour Clutter Removal | |

envelope | Simulation Envelopes of Summary Function | |

linearmarkequal | Mark Connection Function for Multitype Point Pattern on Linear Network | |

predict.ppm | Prediction from a Fitted Point Process Model | |

rMatClust | Simulate Matern Cluster Process | |

pixellate | Convert Spatial Object to Pixel Image | |

dilation | Morphological Dilation | |

quantess | Quantile Tessellation | |

rgbim | Create Colour-Valued Pixel Image | |

layout.boxes | Generate a Row or Column Arrangement of Rectangles. | |

predict.slrm | Predicted or Fitted Values from Spatial Logistic Regression | |

intensity.quadratcount | Intensity Estimates Using Quadrat Counts | |

spruces | Spruces Point Pattern | |

clusterset | Allard-Fraley Estimator of Cluster Feature | |

dilated.areas | Areas of Morphological Dilations | |

plot.psp | plot a Spatial Line Segment Pattern | |

rmh | Simulate point patterns using the Metropolis-Hastings algorithm. | |

closepairs | Close Pairs of Points | |

pixellate.psp | Convert Line Segment Pattern to Pixel Image | |

nnwhich.lpp | Identify Nearest Neighbours on a Linear Network | |

nndist.lpp | Nearest neighbour distances on a linear network | |

rmhmodel.list | Define Point Process Model for Metropolis-Hastings Simulation. | |

rshift | Random Shift | |

marktable | Tabulate Marks in Neighbourhood of Every Point in a Point Pattern | |

rDGS | Perfect Simulation of the Diggle-Gates-Stibbard Process | |

split.ppx | Divide Multidimensional Point Pattern into Sub-patterns | |

rLGCP | Simulate Log-Gaussian Cox Process | |

nnmark | Mark of Nearest Neighbour | |

round.ppp | Apply Numerical Rounding to Spatial Coordinates | |

fryplot | Fry Plot of Point Pattern | |

concatxy | Concatenate x,y Coordinate Vectors | |

collapse.fv | Collapse Several Function Tables into One | |

shift.im | Apply Vector Translation To Pixel Image | |

rGaussPoisson | Simulate Gauss-Poisson Process | |

nnfun | Nearest Neighbour Index Map as a Function | |

is.marked.ppm | Test Whether A Point Process Model is Marked | |

qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model | |

linearpcfdot | Multitype Pair Correlation Function (Dot-type) for Linear Point Pattern | |

segregation.test | Test of Spatial Segregation of Types | |

rMosaicSet | Mosaic Random Set | |

plot.splitppp | Plot a List of Point Patterns | |

rHardcore | Perfect Simulation of the Hardcore Process | |

harmonic | Basis for Harmonic Functions | |

rpoisline | Generate Poisson Random Line Process | |

plot.solist | Plot a List of Spatial Objects | |

nnmap | K-th Nearest Point Map | |

plot.msr | Plot a Signed or Vector-Valued Measure | |

simulate.kppm | Simulate a Fitted Cluster Point Process Model | |

swedishpines | Swedish Pines Point Pattern | |

scan.test | Spatial Scan Test | |

pcfdot.inhom | Inhomogeneous Multitype Pair Correlation Function (Type-i-To-Any-Type) | |

periodify | Make Periodic Copies of a Spatial Pattern | |

pixellate.owin | Convert Window to Pixel Image | |

pppdist | Distance Between Two Point Patterns | |

reach | Interaction Distance of a Point Process | |

rPoissonCluster | Simulate Poisson Cluster Process | |

cauchy.estK | Fit the Neyman-Scott cluster process with Cauchy kernel | |

bw.relrisk | Cross Validated Bandwidth Selection for Relative Risk Estimation | |

F3est | Empty Space Function of a Three-Dimensional Point Pattern | |

lengths.psp | Lengths of Line Segments | |

methods.funxy | Methods for Spatial Functions | |

default.dummy | Generate a Default Pattern of Dummy Points | |

predict.mppm | Prediction for Fitted Multiple Point Process Model | |

nearestsegment | Find Line Segment Nearest to Each Point | |

nnwhich | Nearest neighbour | |

ppp | Create a Point Pattern | |

shift | Apply Vector Translation | |

summary.im | Summarizing a Pixel Image | |

print.ppp | Print Brief Details of a Point Pattern Dataset | |

im | Create a Pixel Image Object | |

methods.slrm | Methods for Spatial Logistic Regression Models | |

simba | Simulated data from a two-group experiment with replication within each group. | |

vertices | Vertices of a Window | |

influence.ppm | Influence Measure for Spatial Point Process Model | |

split.ppp | Divide Point Pattern into Sub-patterns | |

spiders | Spider Webs on Mortar Lines of a Brick Wall | |

lgcp.estpcf | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |

Extract.im | Extract Subset of Image | |

as.box3 | Convert Data to Three-Dimensional Box | |

relrisk.ppp | Nonparametric Estimate of Spatially-Varying Relative Risk | |

rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm. | |

rotate.im | Rotate a Pixel Image | |

plot.kppm | Plot a fitted cluster point process | |

vcov.mppm | Calculate Variance-Covariance Matrix for Fitted Multiple Point Process Model | |

quadratcount | Quadrat counting for a point pattern | |

rcellnumber | Generate Random Numbers of Points for Cell Process | |

summary.ppm | Summarizing a Fitted Point Process Model | |

bronzefilter | Bronze gradient filter data | |

print.owin | Print Brief Details of a Spatial Window | |

linnet | Create a Linear Network | |

ppm.object | Class of Fitted Point Process Models | |

rNeymanScott | Simulate Neyman-Scott Process | |

eroded.areas | Areas of Morphological Erosions | |

rmpoispp | Generate Multitype Poisson Point Pattern | |

quadrat.test.mppm | Chi-Squared Test for Multiple Point Process Model Based on Quadrat Counts | |

multiplicity.ppp | Count Multiplicity of Duplicate Points | |

edge.Ripley | Ripley's Isotropic Edge Correction | |

quantile.im | Sample Quantiles of Pixel Image | |

intersect.owin | Intersection, Union or Set Subtraction of Two Windows | |

summary.owin | Summary of a Spatial Window | |

unnormdensity | Weighted kernel smoother | |

rho2hat | Smoothed Relative Density of Pairs of Covariate Values | |

layerplotargs | Extract or Replace the Plot Arguments of a Layered Object | |

crossdist | Pairwise distances | |

plot.influence.ppm | Plot Influence Measure | |

run.simplepanel | Run Point-and-Click Interface | |

plot.pp3 | Plot a Three-Dimensional Point Pattern | |

summary.anylist | Summary of a List of Things | |

runifdisc | Generate N Uniform Random Points in a Disc | |

K3est | K-function of a Three-Dimensional Point Pattern | |

crossdist.ppp | Pairwise distances between two different point patterns | |

spatstat-internal | Internal spatstat functions | |

nndensity.ppp | Estimate Intensity of Point Pattern Using Nearest Neighbour Distances | |

methods.units | Methods for Units | |

predict.lppm | Predict Point Process Model on Linear Network | |

whist | Weighted Histogram | |

rmhexpand | Specify Simulation Window or Expansion Rule | |

stratrand | Stratified random point pattern | |

tilenames | Names of Tiles in a Tessellation | |

superimpose.lpp | Superimpose Several Point Patterns on Linear Network | |

runifpoint3 | Generate N Uniform Random Points in Three Dimensions | |

distfun | Distance Map as a Function | |

pairs.im | Scatterplot Matrix for Pixel Images | |

sumouter | Compute Quadratic Forms | |

update.rmhcontrol | Update Control Parameters of Metropolis-Hastings Algorithm | |

square | Square Window | |

rmpoint | Generate N Random Multitype Points | |

plot.owin | Plot a Spatial Window | |

pyramidal | Pyramidal Neurons in Cingulate Cortex | |

is.hybrid | Test Whether Object is a Hybrid | |

pppmatching | Create a Point Matching | |

nnfun.lpp | Nearest Neighbour Map on Linear Network | |

methods.ppx | Methods for Multidimensional Space-Time Point Patterns | |

pool.anylist | Pool Data from a List of Objects | |

quadratresample | Resample a Point Pattern by Resampling Quadrats | |

rMaternI | Simulate Matern Model I | |

trim.rectangle | Cut margins from rectangle | |

textureplot | Plot Image Using Texture Fill | |

nndist.ppx | Nearest Neighbour Distances in Any Dimensions | |

update.symbolmap | Update a Graphics Symbol Map. | |

scanpp | Read Point Pattern From Data File | |

psstA | Pseudoscore Diagnostic For Fitted Model against Area-Interaction Alternative | |

simplify.owin | Approximate a Polygon by a Simpler Polygon | |

plot.tess | Plot a tessellation | |

rshift.ppp | Randomly Shift a Point Pattern | |

sessionLibs | Print Names and Version Numbers of Libraries Loaded | |

stienen | Stienen Diagram | |

scaletointerval | Rescale Data to Lie Between Specified Limits | |

unmark | Remove Marks | |

rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |

simplepanel | Simple Point-and-Click Interface Panels | |

print.im | Print Brief Details of an Image | |

sharpen | Data Sharpening of Point Pattern | |

pointsOnLines | Place Points Evenly Along Specified Lines | |

shapley | Galaxies in the Shapley Supercluster | |

tweak.colourmap | Change Colour Values in a Colour Map | |

rknn | Theoretical Distribution of Nearest Neighbour Distance | |

shift.owin | Apply Vector Translation To Window | |

rshift.splitppp | Randomly Shift a List of Point Patterns | |

texturemap | Texture Map | |

plot.lppm | Plot a Fitted Point Process Model on a Linear Network | |

with.hyperframe | Evaluate an Expression in Each Row of a Hyperframe | |

hextess | Hexagonal Grid or Tessellation | |

rotate.psp | Rotate a Line Segment Pattern | |

bind.fv | Combine Function Value Tables | |

rSSI | Simulate Simple Sequential Inhibition | |

objsurf | Objective Function Surface | |

AreaInter | The Area Interaction Point Process Model | |

union.quad | Union of Data and Dummy Points | |

summary.splitppp | Summary of a Split Point Pattern | |

improve.kppm | Improve Intensity Estimate of Fitted Cluster Point Process Model | |

rhohat | Smoothing Estimate of Covariate Transformation | |

tess | Create a Tessellation | |

relrisk | Estimate of Spatially-Varying Relative Risk | |

suffstat | Sufficient Statistic of Point Process Model | |

rpoisppx | Generate Poisson Point Pattern in Any Dimensions | |

zapsmall.im | Rounding of Pixel Values | |

scalardilate | Apply Scalar Dilation | |

quasirandom | Quasirandom Patterns | |

nndist.psp | Nearest neighbour distances between line segments | |

vcov.slrm | Variance-Covariance Matrix for a Fitted Spatial Logistic Regression | |

valid.ppm | Check Whether Point Process Model is Valid | |

runiflpp | Uniform Random Points on a Linear Network | |

rmhmodel.default | Build Point Process Model for Metropolis-Hastings Simulation. | |

simplenet | Simple Example of Linear Network | |

sporophores | Sporophores Data | |

solist | List of Two-Dimensional Spatial Objects | |

rshift.psp | Randomly Shift a Line Segment Pattern | |

will.expand | Test Expansion Rule | |

fitted.ppm | Fitted Conditional Intensity for Point Process Model | |

solutionset | Evaluate Logical Expression Involving Pixel Images and Return Region Where Expression is True | |

with.fv | Evaluate an Expression in a Function Table | |

unique.ppp | Extract Unique Points from a Spatial Point Pattern | |

padimage | Pad the Border of a Pixel Image | |

yardstick | Text, Arrow or Scale Bar in a Diagram | |

plot.scan.test | Plot Result of Scan Test | |

rpoispp3 | Generate Poisson Point Pattern in Three Dimensions | |

rmhmodel | Define Point Process Model for Metropolis-Hastings Simulation. | |

spatialcdf | Spatial Cumulative Distribution Function | |

urkiola | Urkiola Woods Point Pattern | |

runifpoint | Generate N Uniform Random Points | |

rVarGamma | Simulate Neyman-Scott Point Process with Variance Gamma cluster kernel | |

subset.hyperframe | Subset of Hyperframe Satisfying A Condition | |

as.linim | Convert to Pixel Image on Linear Network | |

gridweights | Compute Quadrature Weights Based on Grid Counts | |

rmh.ppm | Simulate from a Fitted Point Process Model | |

rotate.owin | Rotate a Window | |

setcov | Set Covariance of a Window | |

simulate.lppm | Simulate a Fitted Point Process Model on a Linear Network | |

reduced.sample | Reduced Sample Estimator using Histogram Data | |

volume | Volume of an Object | |

symbolmap | Graphics Symbol Map | |

raster.x | Cartesian Coordinates for a Pixel Raster | |

vesicles | Vesicles Data | |

linearKcross.inhom | Inhomogeneous multitype K Function (Cross-type) for Linear Point Pattern | |

transect.im | Pixel Values Along a Transect | |

pcfmulti | Marked pair correlation function | |

nearest.raster.point | Find Pixel Nearest to a Given Point | |

reflect | Reflect In Origin | |

selfcrossing.psp | Crossing Points in a Line Segment Pattern | |

cut.im | Convert Pixel Image from Numeric to Factor | |

split.hyperframe | Divide Hyperframe Into Subsets and Reassemble | |

selfcut.psp | Cut Line Segments Where They Intersect | |

thomas.estpcf | Fit the Thomas Point Process by Minimum Contrast | |

plot.fv | Plot Function Values | |

latest.news | Print News About Latest Version of Package | |

rthin | Random Thinning | |

summary.ppp | Summary of a Point Pattern Dataset | |

print.ppm | Print a Fitted Point Process Model | |

pairwise.family | Pairwise Interaction Process Family | |

rounding | Detect Numerical Rounding | |

runifpointOnLines | Generate N Uniform Random Points On Line Segments | |

rQuasi | Generate Quasirandom Point Pattern in Given Window | |

ippm | Fit Point Process Model Involving Irregular Trend Parameters | |

kppm | Fit Cluster or Cox Point Process Model | |

lineardisc | Compute Disc of Given Radius in Linear Network | |

vcov.kppm | Variance-Covariance Matrix for a Fitted Cluster Point Process Model | |

plot.layered | Layered Plot | |

rotate.ppp | Rotate a Point Pattern | |

superimpose | Superimpose Several Geometric Patterns | |

spatstat-deprecated | Deprecated spatstat functions | |

summary.psp | Summary of a Line Segment Pattern Dataset | |

unitname | Name for Unit of Length | |

rescue.rectangle | Convert Window Back To Rectangle | |

redwoodfull | California Redwoods Point Pattern (Entire Dataset) | |

rmhcontrol | Set Control Parameters for Metropolis-Hastings Algorithm. | |

as.function.im | Convert Pixel Image to Function of Coordinates | |

cdf.test.mppm | Spatial Distribution Test for Multiple Point Process Model | |

redwood | California Redwoods Point Pattern (Ripley's Subset) | |

is.stationary | Recognise Stationary and Poisson Point Process Models | |

effectfun | Compute Fitted Effect of a Spatial Covariate in a Point Process Model | |

rmhmodel.ppm | Interpret Fitted Model for Metropolis-Hastings Simulation. | |

varblock | Estimate Variance of Summary Statistic by Subdivision | |

summary.listof | Summary of a List of Things | |

intersect.tess | Intersection of Two Tessellations | |

rStrauss | Perfect Simulation of the Strauss Process | |

ppm.ppp | Fit Point Process Model to Point Pattern Data | |

bdist.points | Distance to Boundary of Window | |

quadscheme | Generate a Quadrature Scheme from a Point Pattern | |

rotate | Rotate | |

vcov.ppm | Variance-Covariance Matrix for a Fitted Point Process Model | |

crossdist.pp3 | Pairwise distances between two different three-dimensional point patterns | |

gordon | People in Gordon Square | |

waka | Trees in Waka national park | |

plot.bermantest | Plot Result of Berman Test | |

colourmap | Colour Lookup Tables | |

plot.imlist | Plot a List of Images | |

update.kppm | Update a Fitted Cluster Point Process Model | |

quadrat.test | Dispersion Test for Spatial Point Pattern Based on Quadrat Counts | |

japanesepines | Japanese Pines Point Pattern | |

quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model | |

waterstriders | Waterstriders data. Three independent replications of a point pattern formed by insects. | |

runifpointx | Generate N Uniform Random Points in Any Dimensions | |

fitted.mppm | Fitted Conditional Intensity for Multiple Point Process Model | |

rose | Rose Diagram | |

plot.fasp | Plot a Function Array | |

spokes | Spokes pattern of dummy points | |

plot.quadratcount | Plot Quadrat Counts | |

model.images | Compute Images of Constructed Covariates | |

diameter.boxx | Geometrical Calculations for Multi-Dimensional Box | |

pcf | Pair Correlation Function | |

perimeter | Perimeter Length of Window | |

ripras | Estimate window from points alone | |

shift.psp | Apply Vector Translation To Line Segment Pattern | |

linearKcross | Multitype K Function (Cross-type) for Linear Point Pattern | |

lppm | Fit Point Process Model to Point Pattern on Linear Network | |

Ginhom | Inhomogeneous Nearest Neighbour Function | |

rpoispp | Generate Poisson Point Pattern | |

vargamma.estpcf | Fit the Neyman-Scott Cluster Point Process with Variance Gamma kernel | |

methods.layered | Methods for Layered Objects | |

boundingbox | Bounding Box of a Window, Image, or Point Pattern | |

reload.or.compute | Compute Unless Previously Saved | |

parres | Partial Residuals for Point Process Model | |

psstG | Pseudoscore Diagnostic For Fitted Model against Saturation Alternative | |

split.im | Divide Image Into Sub-images | |

rpoislpp | Poisson Point Process on a Linear Network | |

identify.ppp | Identify Points in a Point Pattern | |

rat | Ratio object | |

simulate.ppm | Simulate a Fitted Gibbs Point Process Model | |

Gcom | Model Compensator of Nearest Neighbour Function | |

methods.objsurf | Methods for Objective Function Surfaces | |

murchison | Murchison gold deposits | |

affine.owin | Apply Affine Transformation To Window | |

plot.textstring | Plot a Text String | |

hyperframe | Hyper Data Frame | |

as.layered | Convert Data To Layered Object | |

rDiggleGratton | Perfect Simulation of the Diggle-Gratton Process | |

rlabel | Random Re-Labelling of Point Pattern | |

simdat | Simulated Point Pattern | |

inforder.family | Infinite Order Interaction Family | |

solapply | Apply a Function Over a List and Obtain a List of Objects | |

is.lpp | Test Whether An Object Is A Point Pattern on a Linear Network | |

linearKdot | Multitype K Function (Dot-type) for Linear Point Pattern | |

plot.colourmap | Plot a Colour Map | |

methods.box3 | Methods for Three-Dimensional Box | |

rStraussHard | Perfect Simulation of the Strauss-Hardcore Process | |

plot.plotppm | Plot a plotppm Object Created by plot.ppm | |

rmhstart | Determine Initial State for Metropolis-Hastings Simulation. | |

vargamma.estK | Fit the Neyman-Scott Cluster Point Process with Variance Gamma kernel | |

stieltjes | Compute Integral of Function Against Cumulative Distribution | |

triplet.family | Triplet Interaction Family | |

subfits | Extract List of Individual Point Process Models | |

simulate.slrm | Simulate a Fitted Spatial Logistic Regression Model | |

subset.ppp | Subset of Point Pattern Satisfying A Condition | |

model.frame.ppm | Extract the Variables in a Point Process Model | |

adaptive.density | Intensity Estimate of Point Pattern Using Tessellation | |

dfbetas.ppm | Parameter influence measure | |

discs | Union of Discs | |

Kmodel.kppm | K Function or Pair Correlation Function of Cluster Model or Cox model | |

pairdist.default | Pairwise distances | |

DiggleGatesStibbard | Diggle-Gates-Stibbard Point Process Model | |

Ldot | Multitype L-function (i-to-any) | |

Kdot.inhom | Inhomogeneous Multitype K Dot Function | |

default.expand | Default Expansion Rule for Simulation of Model | |

boxx | Multi-Dimensional Box | |

crossdist.psp | Pairwise distances between two different line segment patterns | |

duplicated.ppp | Determine Duplicated Points in a Spatial Point Pattern | |

delaunay.network | Linear Network of Delaunay Triangulation or Dirichlet Tessellation | |

Gest | Nearest Neighbour Distance Function G | |

Hybrid | Hybrid Interaction Point Process Model | |

diameter.linnet | Circumradius and Diameter of a Linear Network | |

delaunay | Delaunay Triangulation of Point Pattern | |

Kest.fft | K-function using FFT | |

Hest | Spherical Contact Distribution Function | |

eval.linim | Evaluate Expression Involving Pixel Images on Linear Network | |

istat | Point and Click Interface for Exploratory Analysis of Point Pattern | |

append.psp | Combine Two Line Segment Patterns | |

compatible.fasp | Test Whether Function Arrays Are Compatible | |

methods.kppm | Methods for Cluster Point Process Models | |

intensity | Intensity of a Dataset or a Model | |

Extract.influence.ppm | Extract Subset of Influence Object | |

Gres | Residual G Function | |

affine | Apply Affine Transformation | |

berman.test | Berman's Tests for Point Process Model | |

linfun | Function on a Linear Network | |

fitin.ppm | Extract the Interaction from a Fitted Point Process Model | |

bw.stoyan | Stoyan's Rule of Thumb for Bandwidth Selection | |

methods.rho2hat | Methods for Intensity Functions of Two Spatial Covariates | |

letterR | Window in Shape of Letter R | |

logLik.ppm | Log Likelihood and AIC for Point Process Model | |

blur | Apply Gaussian Blur to a Pixel Image | |

density.splitppp | Kernel Smoothed Intensity of Split Point Pattern | |

colourtools | Convert and Compare Colours in Different Formats | |

pixellate.ppp | Convert Point Pattern to Pixel Image | |

integral.im | Integral of a Pixel Image | |

hyytiala | Scots pines and other trees at Hyytiala | |

humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |

fitted.slrm | Fitted Probabilities for Spatial Logistic Regression | |

dendrite | Dendritic Spines Data | |

as.ppm | Extract Fitted Point Process Model | |

imcov | Spatial Covariance of a Pixel Image | |

lohboot | Bootstrap Confidence Bands for Summary Function | |

nestsplit | Nested Split | |

nztrees | New Zealand Trees Point Pattern | |

ppp.object | Class of Point Patterns | |

pairdist | Pairwise distances | |

quadscheme.logi | Generate a Logistic Regression Quadrature Scheme from a Point Pattern | |

slrm | Spatial Logistic Regression | |

plot.texturemap | Plot a Texture Map | |

owin | Create a Window | |

residuals.mppm | Residuals for Point Process Model Fitted to Multiple Point Patterns | |

rcell | Simulate Baddeley-Silverman Cell Process | |

linim | Create Pixel Image on Linear Network | |

relrisk.ppm | Parametric Estimate of Spatially-Varying Relative Risk | |

rThomas | Simulate Thomas Process | |

rpoislinetess | Poisson Line Tessellation | |

spatstat-package | The Spatstat Package | |

sidelengths.owin | Side Lengths of Enclosing Rectangle of a Window | |

tiles | Extract List of Tiles in a Tessellation | |

update.ppm | Update a Fitted Point Process Model | |

rescale.im | Convert Pixel Image to Another Unit of Length | |

Smooth.msr | Smooth a Signed or Vector-Valued Measure | |

ord.family | Ord Interaction Process Family | |

thomas.estK | Fit the Thomas Point Process by Minimum Contrast | |

methods.boxx | Methods for Multi-Dimensional Box | |

add.texture | Fill Plot With Texture | |

Strauss | The Strauss Point Process Model | |

alltypes | Calculate Summary Statistic for All Types in a Multitype Point Pattern | |

compareFit | Residual Diagnostics for Multiple Fitted Models | |

as.solist | Convert List of Two-Dimensional Spatial Objects | |

as.lpp | Convert Data to a Point Pattern on a Linear Network | |

chicago | Chicago Street Crime Data | |

clickbox | Interactively Define a Rectangle | |

envelope.lpp | Envelope for Point Patterns on Linear Network | |

dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model | |

distfun.lpp | Distance Map on Linear Network | |

Kmodel | K Function or Pair Correlation Function of a Point Process Model | |

flu | Influenza Virus Proteins | |

ewcdf | Weighted Empirical Cumulative Distribution Function | |

chorley | Chorley-Ribble Cancer Data | |

methods.fii | Methods for Fitted Interactions | |

localKinhom | Inhomogeneous Neighbourhood Density Function | |

pairdist.ppx | Pairwise Distances in Any Dimensions | |

pixelcentres | Extract Pixel Centres as Point Pattern | |

box3 | Three-Dimensional Box | |

plot.hyperframe | Plot Entries in a Hyperframe | |

linearpcfcross | Multitype Pair Correlation Function (Cross-type) for Linear Point Pattern | |

ppx | Multidimensional Space-Time Point Pattern | |

nncross | Nearest Neighbours Between Two Patterns | |

rescale.owin | Convert Window to Another Unit of Length | |

mppm | Fit Point Process Model to Several Point Patterns | |

plot.cdftest | Plot a Spatial Distribution Test | |

shift.ppp | Apply Vector Translation To Point Pattern | |

pool.fasp | Pool Data from Several Function Arrays | |

localK | Neighbourhood density function | |

Extract.layered | Extract or Replace Subset of a Layered Object | |

Gmulti | Marked Nearest Neighbour Distance Function | |

Softcore | The Soft Core Point Process Model | |

Extract.listof | Extract or Replace Subset of a List of Things | |

Extract.owin | Extract Subset of Window | |

integral.msr | Integral of a Measure | |

contour.imlist | Array of Contour Plots | |

linearmarkconnect | Mark Connection Function for Multitype Point Pattern on Linear Network | |

predict.kppm | Prediction from a Fitted Cluster Point Process Model | |

pp3 | Three Dimensional Point Pattern | |

pcf3est | Pair Correlation Function of a Three-Dimensional Point Pattern | |

print.quad | Print a Quadrature Scheme | |

timed | Record the Computation Time | |

rpoint | Generate N Random Points | |

tile.areas | Compute Areas of Tiles in a Tessellation | |

rotmean | Rotational Average of a Pixel Image | |

summary.solist | Summary of a List of Spatial Objects | |

rsyst | Simulate systematic random point pattern | |

residuals.ppm | Residuals for Fitted Point Process Model | |

rjitter | Random Perturbation of a Point Pattern | |

quantile.ewcdf | Quantiles of Weighted Empirical Cumulative Distribution Function | |

pairsat.family | Saturated Pairwise Interaction Point Process Family | |

addvar | Added Variable Plot for Point Process Model | |

crossing.psp | Crossing Points of Two Line Segment Patterns | |

psst | Pseudoscore Diagnostic For Fitted Model against General Alternative | |

rstrat | Simulate Stratified Random Point Pattern | |

rCauchy | Simulate Neyman-Scott Point Process with Cauchy cluster kernel | |

linearpcfdot.inhom | Inhomogeneous Multitype Pair Correlation Function (Dot-type) for Linear Point Pattern | |

nsegments | Number of Line Segments in a Line Segment Pattern | |

is.multitype.ppm | Test Whether A Point Process Model is Multitype | |

No Results! |

## Last month downloads

## Details

Nickname | Ides of March |

Date | 2015-02-27 |

License | GPL (>= 2) |

URL | http://www.spatstat.org |

LazyData | true |

NeedsCompilation | yes |

ByteCompile | true |

Packaged | 2015-02-27 00:43:10 UTC; adrian |

Repository | CRAN |

Date/Publication | 2015-02-27 07:32:22 |

imports | abind , deldir (>= 0.0-21) , goftest , Matrix , mgcv , polyclip (>= 1.3-0) , tensor |

depends | base (>= 3.1.1) , graphics , grDevices , R (>= 3.1.1) , stats , utils |

suggests | gsl , locfit , maptools , RandomFields (>= 3.0.0) , rpanel , sm , spatial , tkrplot |

Contributors | Rolf Turner, Adrian Baddeley, Ege Rubak |

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